Zhang, Peng; Song, Dawei; Wang, Jun and Hou, Yuexian
(2013).
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(Version of Record)
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| URL: | http://dl.acm.org/citation.cfm?doid=2484028.248412... |
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| DOI (Digital Object Identifier) Link: | https://doi.org/10.1145/2484028.2484127 |
| Google Scholar: | Look up in Google Scholar |
Abstract
It has been recognized that, when an information retrieval (IR) system achieves improvement in mean retrieval effectiveness (e.g. mean average precision (MAP)) over all the queries, the performance (e.g., average precision (AP)) of some individual queries could be hurt, resulting in retrieval instability. Some stability/robustness metrics have been proposed. However, they are often defined separately from the mean effectiveness metric. Consequently, there is a lack of a unified formulation of effectiveness, stability and overall retrieval quality (considering both). In this paper, we present a unified formulation based on the bias-variance decomposition. Correspondingly, a novel evaluation methodology is developed to evaluate the effectiveness and stability in an integrated manner. A case study applying the proposed methodology to evaluation of query language modeling illustrates the usefulness and analytical power of our approach.
| Item Type: | Conference or Workshop Item |
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| Copyright Holders: | 2013 ACM |
| Extra Information: | SIGIR '13
Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval ACM New York, NY, 2013 ISBN: 978-1-4503-2034-4 |
| Keywords: | bias-variance; decomposition; effectiveness; stability; robustness; evaluation |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Item ID: | 38094 |
| Depositing User: | Dawei Song |
| Date Deposited: | 02 Aug 2013 09:20 |
| Last Modified: | 07 Dec 2018 23:06 |
| URI: | http://oro.open.ac.uk/id/eprint/38094 |
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